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  "Title": "Multi-Level Vector Autoregression",
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  "Description": "Estimates the multi-level vector autoregression model on\ntime-series data. Three network structures are obtained:\ntemporal networks, contemporaneous networks and\nbetween-subjects networks.",
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  "Date/Publication": "2026-03-16 02:39:11 UTC",
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    "message": "Change variance=\"empirical\" to use model partial correlation structure scaled by empirical SDs\n\nInstead of using the full empirical residual covariance, variance=\"empirical\"\nnow uses SD %*% cov2cor(solve(kappa_i)) %*% SD, preserving the model's\npartial correlation structure while scaling by person-specific empirical\nresidual standard deviations.\n\nCo-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>\n",
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      "title": "Multi-Level Gaussian Graphical Model Estimation",
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        "plot.mlGGM",
        "print.mlGGM",
        "summary.mlGGM"
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    {
      "page": "mlVAR",
      "title": "Multilevel VAR Estimation for Multiple Time Series",
      "topics": [
        "mlVAR",
        "predict.mlVAR",
        "residuals.mlVAR",
        "resimulate",
        "resimulate.mlVAR"
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      "topics": [
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        "randomEffects"
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      "title": "Multilevel VAR Estimation for Multiple Time Series",
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        "summary.mlVAR0"
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      ]
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        "summary.mlVARsample"
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        "plot.mlVARsim"
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        "summary.mlVAR"
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